Wednesday, August 31, 2016

Earlier this summer, I went to a Gordon Research Conference
on Ocean Global Change
Biology at the invitation of Sinead Collins. I don’t typically work on
oceans, and so the fit might not see obvious, but the relevant part was that
the field has taken on a distinctly evolutionary flavor. It turns out that many
ocean biologists are now focusing on adaptive responses of marine organism to
climate change, especially ocean acidification. It was a wonder to sit through
talk after talk of studies assessing the potential for (usually) plankton to
adapt to either increased acidity or warmer water. Even the talks that didn’t
focus on evolution almost always referred to it in an informed and considered
manner. I had previously been to a similar conference 8 or so years earlier,
and that time I saw only the barest hint of evolution – so this was an exciting
change. Yet it isn’t in my nature to be complementary without qualification (or
critical without qualification) – and the same will apply here.

I couldn't decide my favorite photo so here are Google's favorites.

In 1961, G. Evelyn Hutchinson wrote a paper titled The Paradox
of the Plankton, in which he discussed the apparent paradox that so many
species of plankton coexist even though they compete for similar nutrients –
ostensibly in contradiction to the principle of competitive exclusion. I wish
to here introduce – by way of verbal analogy – The Trouble with the Plankton,
which is somewhat related to the Paradox of the Plankton in its emphasis on
variation.

Stated simply, I suggest that Ocean Global Change biologists
should stop worry about whether or not plankton will evolve in response to
climate change – they will! Unlike many other organisms, evolution is not normally
going to be a problem for phytoplankton (or even zooplankton) – for four main
reasons.

I couldn't decide my favorite photo so here are Google's favorites.

1. Most species of plankton are extremely abundant,
which means that standing genetic variation will be huge, as will be mutational
inputs. In short, genetic variation – the raw material for evolution – should be
massive for essentially all marine plankton.

2. Most species (and indeed many populations and
even individuals) of plankton experience dramatic fluctuations in environmental
conditions across space (vertical and horizontal) and time (hourly, daily,
seasonally). This past variation in environmental conditions means that past
selection will have tested (and sometimes favored) adaptive genetic variants
for a wide variety of conditions – again maintaining high genetic variation in
adaptively-relevant variants.

3. The rate of abiotic environmental change in the
ocean is very modest not only in relation to the above-noted past and present
spatiotemporal variation in selection but also in relation to the generation
time of phytoplankton (and zooplankton). As a result, the per-generation shift
in the environment owing to climate change will be tiny in relation to the
potential evolutionary speed of plankton.

4. Many plankton show adaptive plasticity in
response to different abiotic conditions, including acidity and temperature.
This plasticity should buffer the immediate negative effects of environmental change
and thus allow further time for evolution.

Fitting these expectations, every study at the conference
showed strong evolution in response to dramatically altered environments (often
much more so than projections for climate change), despite often extremely limited
starting genetic variation. Many studies of freshwater plankton have similarly
shown that evolution in even small experimental populations can accomplish – in
only a single summer – full adaptation to environmental changes projected to
take place over decades. And “resurrection” studies that bring past zooplankton
to life also show rapid responses to all sorts of environmental changes. So I
suggest that we don’t need more studies asking “can plankton adapt to climate
change” – they can – simple as that.

However, I do think that further evolutionary studies are
critical for Ocean Global Change Biology – I merely suggest that their focus
should be a bit different.

1. Studies could profitably ask “what are the
consequences of the evolution of plankton for communities and ecosystems.” I
image that the evolution of plankton in response to climate change could
dramatically alter their relationship with other species in the community. Some
of those species, especially those with longer generation times, such as
planktivorous fish, might have trouble responding adaptively. Thus, it would be
fascinating to take those experimentally evolved lines of plankton and see how
they interact with other key species in the community.

Here you can find more arguments for considering the ecological effects of evolution.

2. Although most (maybe all) plankton will have no
trouble adapting to abiotic changes associated with climate change, they might
have trouble adapting to some correlated biotic changes. For instance,
planktivorous fish might dramatically change in abundance with climate change,
which might then impact plankton populations in ways that are strongly modified
by evolution.

Of course, the general statements above are not intended to
imply that all marine invertebrates will easily adapt to climate change. Corals
for instance seem to be near their physiological (and evolutionary) limits
already and might have no suitable genetic variation to respond to selection.
Of course, changing their symbionts might be another way to adapt – although that
too will have limits. Also, species in already extreme conditions (e.g., the hottest
or most acidic water) might not be able to persist locally as those conditions
change. Indeed, acid rain caused the extirpation of many (but not all) plankton
species – and very warm (or cold) temperatures could do the same.

Regardless of whether or not I am correct that
plankton will have little trouble adapting, I do think evolutionary studies are
extremely informative. I can’t wait to be invited back for the next Gordon
Research Conference – or perhaps I won’t be given this post.

Thursday, August 25, 2016

I was recently talking about my PhD work with some new colleagues in the Department, when I realized I was getting a little bit nostalgic. Working in Trinidad was a great experience, and I had a lot of fun doing all the small and large experiments, but in reality one of the things I missed the most was one little fish – and no, it was not the Trinidadina guppy.

Fig. 1. I guess that they do look like they are smiling...

During one of my first trips to the island, I got to familiarize myself with the very charismatic jumping wabeen, or more formally Rivulus hartii. It is hard to explain why I got so fond of this little guy, but many people that have worked with Rivulus share the same feeling – although many others don't even want to hear about them, and you will know why soon. My love for Rivulus, like any other love relationship, went through ups and downs. Rivulus tend to jump (a lot!), and that is why their local name is jumping wabeen. You cannot leave one inch of the aquaria uncovered because one by one they will jump out, and you will end up with a parade of jumping little blobs on your lab floor. Those were the days I hated working with Rivulus. Then were the days that they were sitting quietly in their aquaria, looking straight at me with their huge, baby eyes and big smile (or at least that is how their mouth looks to me, see for yourself in Fig. 1). Those were the days when I loved working with Rivulus. But then again were the days where you needed to transfer two of them to a new facility, and make the mistake to put different sizes together. You still arrive to your destination with the two fish, but one will definitely be inside the other – in a way, it was similar to the painting " Big fish eat small fish" by Pieter Bruegel the Elder (Fig. 2), where pretty much every fish is munching on a smaller one, which is munching on a yet smaller one. Those were also the days I hated working with Rivulus.

Fig. 2. Big fish eat small fish by Pieter Bruegel the Elder. I really like the walking fish munching on a smaller one.

The fact that Rivulus are relatively small and voracious, and coexist with the Trinidadian guppy has been of great interest to many ecologists and evolutionary biologists – among which I can certainly include myself. In particular, I was very interested in how the interaction between guppies and Rivulus could be affected by a guppy specific parasite, Gyrodactylus (you can see some of my previous blogs about guppies and Gyros). But before I go into the details of that experiment let me talk a little bit more about Rivulus' ecology. Adult Rivulus are much larger than adult guppies (the largest Rivulus are almost three times larger than the largest guppies!) and are strict predators, foraging mainly on everything that fits in their mouth, like invertebrates and small ﬁsh, including juvenile guppies. Juvenile Rivulus, on the other hand, are of similar size as guppies, and directly compete with guppies for shelter and food (i.e. aquatic invertebrates). Previous studies have also shown that the presence of guppies decreases the growth rate of size-mathced juvenile Rivulus – through resource competition – but dramatically increases the growth rate of adult Rivulus, through guppy predation on Rivulus young, and the release of adult Rivulus from intra-speciﬁc competition. Given these strong interactions between the various classes of Rivulus and guppies, it was very conceivable that a guppy-specific parasite could tip the balance in Rivulus' favor. Or at least that was my initial hypothesis.

I designed an experiment that would allow me to break down the different effects of Rivulus, guppies and the guppy-specific ectoparasite, Gyrodactylus, could have on both fish species' growth. The experiment consisted of ﬁve experimental treatments: guppies only (GO); guppies and Gyrodactylus (GG); guppies, Gyrodactylus, and Rivulus (GGR); guppies and Rivulus (GR); and Rivulus only (RO). I made sure that the total biomass was, if not equal, very similar among the different replicates, and put the sized-matched fish in mesocosms that replicate natural streams (i.e. lots of gravel with invertebrates and algae, flowing water, etc.), and came back 20 days later to see how much guppies and Rivulus had grown in the presence of each other and/or the parasite. (if you want to check out the full article with the detailed methods you can do it here).

The results were somehow surprising. Remember that I said that my hypothesis was that Gyrodactylus was going to tip the balance in favor of Rivulus. I found that the presence of Gyrodactylus parasites decreased female guppy growth, and this effect was much stronger than the effect of Rivulus (Fig. 3), but more intriguingly I found a very strong antagonistic interaction: Gyrodactylus reduced guppy growth in the absence but not the presence of Rivulus. In short, the relative effect of Gyrodactylus on the growth of guppies was much greater than that of the competitor (and potential predator), but the two effects were strongly interactive. In other words, Gyrodactylus did not significantly affect the interaction between Rivulus and guppies!!!

Fig. 3. Gyrodactylus did not influence Rivulus-guppy competition, but certainly had an effect on its own!

In the paper, my co-authors and I suggest two potential mechanisms that may have prevented Gyrodactylus from influencing the guppy-Rivulus interaction. First, the coexistence between guppies and Rivulus has been commonly viewed as a balance between predation and competition, with guppies being the better competitors, but large adult Rivulus actively preying upon juvenile guppies. So, although we did ﬁnd a trend for a decrease in growth of Rivulus in the presence of size-matched guppies, this was not signiﬁcantly different from the Rivulus-only control. It is possible that under these experimental conditions competition is lessened due to relatively low ﬁsh density per mesocosms; however, an alternative possibility is that Rivulus grow larger than guppies and shift their diet towards terrestrial prey that are too large for guppies to eat, releasing them from resource competition. Indeed, at the end of the experiment Rivulus in the mixed-species treatment were almost three times larger than female guppies, despite being of similar size as the largest female guppies in the mesocosms at the beginning of the experiment. Second, as an apparently adaptive response to reduce Rivulus predation on juvenile guppies, these increase their growth rate when exposed to chemical cues from adult Rivulus. Guppies might thus show a phenotypic response to Rivulus as a potential predator, and not a competitor. Even though the Rivulus in our experiment were not large enough to eat the guppies, the presence of small Rivulus is presumably a reliable cue of the likely presence of larger Rivulus. If guppies increased their growth in response to chemical cues signaling the presence of Rivulus, this would have partially counteracted the negative effects of parasitism on guppy growth, consistent with our observation that female guppy in the presence of Gyrodactylus and Rivulus was intermediate between guppy-only and guppy–Gyrodactylus treatments.

I certainly think that these results generate several important insights into the nature of guppy–Gyrodactylus–Rivulus interactions and, more generally, food web interactions. But these results have also helped me better understand what is going on in the small and shallow tributaries of Trinidad, where I spent several nights and days exploring and collecting fish.

Rivulus are more easily collected at night, so Pierson Hill had this great picture of one of those days I helped them collect Rivs for David Reznick's FIBR project.

Saturday, August 6, 2016

Sitting on the beach tonight playing chess and
drinking wine with my postdoc Yoel Stuart, I couldn’t help but worry about
tomorrow. Tomorrow morning is a crucial step in an experiment that colleagues
and I have planned for years. The idea came in 2008, but took years to get all
the pieces in place. One NSF grant was funded, and completed in three years, to
get preliminary data to plan a second NSF grant that was also funded to do this
experiment. We also had to convince the Howard Hughes Medical Institute to
build a huge fish room in a remote field station (Bamfield Marine Sciences Center).
Then we had to get permits. Then we spent a year and a half breeding fish.
Field trips to collect parents, personnel time to take care of F1s, a grad
student RA position to live in Bamfield and cross fish to make F2s, then more
personnel time to breed the fish. Then, weeks spent sewing a kilometer of
netting into little cages, and cutting up and assembling two and a half
kilometers of PVC piping into cage frames. A week of field work with six people
to install the 160 cages in 4 locations on northern Vancouver Island.

Ready for stickleback - but will it work?

Years of preparation, multiple grants, and now a
moment of truth: will the juvenile fish survive the 5 hour drive north over
rough dirt roads, from their rearing facility at BMSC to their grandparents’
native lakes and streams? If not, the intended experiment will have failed
before it really began. No data. No conclusions. (Admittedly, this upcoming
transplant is just one of 8 planned transplants in this project, so we have the
opportunity to learn, adjust, and recover.)

Naturally,
I am thinking a lot about failure tonight. Not just the potential failure of
this transplant experiment in particular, but broader questions of failure in
science. Evening on a beach is a good time and place for broad contemplation.
Pachena Beach, especially, with its slanting sunlight light through drifting
fog and tall trees.

So, I find myself wondering?

How many attempted experiments
failed for logistical reasons and just never get reported?

What are the various reasons
why we fail?

What do we learn from our various
experimental failures?

When is failure a productive
source of insight, versus a plain old flop?

I started to also write the question: “How do we
best insulate ourselves from failure?”, then paused. The fact is, failure is
not uniformly bad. Sure, too many high-risk projects may leave us empty-handed.
But, over-attention to failure can be bad too. Fear of failure can drive some
people to paralysis. Others may take risks but falsify the results of failed
attempts. Still others opt to rely exclusively on ‘safe’ projects, that often
cover well-trodden ground and thus teach us little that is new or
interesting.This leads to the
conclusion that we shouldn’t insulate ourselves from failure. Instead, we need
to become good judges of scientific risk, choosing an intellectual ‘portfolio’
of projects that combine an appropriate range of risks. A mix of high- and
low-risk.

So instead of asking how to avoid failed
experiments, I would rather ask how we can teach aspiring students to judge
risk in advance, and how to be brave but not foolhardy in taking on projects.
This is surely fodder for an entire book. Such books probably even exist. I
don’t know, because I am sitting on a beach without wifi (thank goodness).
Lacking access to the web, I will attempt a much more modest goal with this
blog post. I will attempt a taxonomy of scientific failures. And, I will
illustrate these failures with vignettes from my own experience. Consider this
my mea culpa of failed attempts at
science. Hopefully it will be both cathartic for me, entertaining for you, and
get the right karma in place to keep my north-bound fish alive in the coming
day.

Spoiler alerts: the following contains some
references to events in Game of Thrones. If you don’t care, fine, you can just
ignore the ‘literary’ references and focus on the ideas and biology. If you’ve
read the books or seen the TV show, fine. If you haven’t yet read these but
intend to, then you might want to skip down to the line saying . Sorry.

Failure category 1: The Viserys Targaryen. For
“Game of Thrones” aficionados, Viserys is a minor but entertaining character:
the child of a dethroned king who connived to reconquer his ancestral kingdom.
He thought he had a plan to do so, but sort of bumbled along and didn’t implement
things very deftly, with the result that his plan fell apart (and he had molten
gold poured over his head). Had he thought a bit more clearly, he should have
foreseen some of these problems. So, I’ll invoke Viserys to represent a very
common category of failure, in which the basic plan sees reasonable at a
cursory glance, but the details and implementation don’t live up to
expectations. This is perhaps the most common and most avoidable form of
failure. You come away empty-handed, except perhaps with a better understanding
of how NOT to design an experiment (which is indeed useful).

Viserys and his golden crown.

Failure category 2: The Wise Masters. Continuing
with our literary theme (if you choose to call it that), the Wise Masters
really thought that they had a well-worked out path to their goals. They simply
overlooked a colossal and totally unexpected fact: their adversary had massive
pet dragons. Oops. Not really something you can plan ahead for. So, we’ll give
the Wise Masters a nod in naming failures in which truly unforeseeable problems
undermine otherwise well-thought-through plans. These may be more common than
we like to think, but are inherently less avoidable than the Viserys Targaryen.
Admittedly, these two kinds of failure are going to overlap a bit: an unexpected
‘dragon’ to one researcher might be foreseeable to another. This is why you
should show your research plan to colleagues and mentors as much as possible –
someone out there may anticipate your particular dragon.

The Wise Masters are about to meet Drogon the dragon

Failure category 3: The Eddard Stark. This one
is simple: many beautiful hypotheses are slain by ugly facts. Much like the
idealistic Eddard Stark tried to govern but was undermined by the sad fact that
political reality was different than he naively believed. We could equally name
this after his son, Robb Stark, King of the North, who went to a wedding of an
aggrieved subordinate, incorrectly assuming that the rules of hospitality could
be trusted. This is the kind of failure that philosophers of science have
indeed written volumes about: we have hypotheses about how the world works. We
design experiments or other kinds of studies to test these hypotheses (or their
null alternatives). Sometimes we ‘fail to reject the null hypothesis’. This is
a failure in the entirely constructive sense that we do indeed learn something.
Unlike the previous two kinds of failure, we actually get data, we analyze it,
and we were wrong about something. We learn something about in the process.

Ned Stark pays the price for honor - or is it naivete?

Failure category 4. The Great Houses. The core
of the book series of course, is the battle for political dominion among
several families (the ‘Great Houses’), which are so focused on their squabbles
that they totally overlooked a fundamental fact that their collective existence
was threatened by semi-human magical winter beings. Kind of an important thing
to know about, and they had some warnings thanks to the Night’s Watch.
Likewise, every now and then we scientists get a hint of something really
substantially new and surprising, and we often are so focused on our previous
agenda that we overlook the hint, not recognizing the importance of what we
just saw. This is perhaps the most problematic failure, because it represents
lost opportunities for novel insight.

To summarize, our taxonomy of failures includes
1) poor planning leading to avoidable problems, 2) unexpected interference, 3)
incorrect hypotheses, and 4) overlooking important things. I’ve probably failed
to include something here – feel free to chime in on the comments.

Now, in the spirit of full disclosure I want to
give a few examples of my own, in the hope these will help students or
colleagues avoid similar mistakes, raise awareness that one’s career can
survive failures (I think…), and perhaps even entertain.

Vignette 1: When I pulled a ‘Viserys Targaryen’,
also known among my graduate students and postdocs as ‘Bolnick’s folly’. When I
first started working on stickleback I did an experiment in one half of an
hour-glass shaped lake. I later returned to that lake to examine the other half in more
detail, discovering that the stickleback in the larger deeper basin and shallow
small basin were dramatically different in diet (more so than the famed
benthic-limnetic species pairs of stickleback). Yet despite this massive
ecological difference, their phenotypes were only subtly divergent. Why not
diverge as much as the species pairs?

Ormond and Dugout
Lakes on Vancouver Island. The narrow marsh separating them can be clearly
seen. The barrier to dispersal was built across that marsh.

Presumably because the two lake basins
are connected by a narrow marsh(~20
meters wide) that permits free movement of migrants between the basins (Bolnick
et al 2008 Biol J. Linn Soc.). So, obvious experiment: create a barrier to
movement, and track the subsequent emergence of genetic and phenotypic
differences, then remove the barrier and watch those differences collapse. All
I needed was a barrier. So, in 2007 I found myself back in British Columbia
with two field assistants and an extra week on our hands between other tasks. I
had planned ahead and obtained permission to build a barrier and leave it in
for a decade (~10 generations). All that remained was to make the barrier
reality. We installed sturdy steel 8 foot tall fence posts in a transect across
the entire neck of marsh connecting the two lakes. We attached chain-link
fencing, carefully sunk into the substrate of the marsh all the way across (~30
meters wide including semi-marshy habitat that probably rarely allows
migration, but we had to block that just in case). We then attached a fine
screen to this fencing - We had to build it with fine enough mesh to prevent
passage even of juvenile fish, so we used a sturdy type of coarse mosquito
netting. One layer of netting on either side of the fence. Then we installed
another layer of chain link fencing to sandwich a mosquito net in between, for
added strength. All of this was buried deeply into the substrate, which
involved several days of lying face down in muck in our wetsuits cutting into
the peat with a saw. The end product looked satisfyingly sturdy (Fig. 2).

Building the barrier
across the marsh.

Now, I knew all along that water flowed from the
smaller basin into the larger one – imperceptibly slowly, but still flowing.
And I knew therefore that the fence would get water pressure and sediment
build-up. But I figured water would keep seeping through, maybe raise the water
level a bit. I knew this might be wrong, and the whole thing might fall apart
due to water pressure. But, it was a risk I was willing to take.

Ten months later when we returned to the site,
it was a mess. The barrier had clearly worked at keeping stuff from moving
between the lakes – including small sediment, which built up. The fence became
a dam. And those 8’foot tall fence posts were stuck firmly in the sediment (job
well done!) but were not up to the task of holding back a 4 hectare lake. They
bent over like straws. We found the whole fence lying on its side (Fig. 3), not because the
posts came out but because the steel beams bent to nearly 90 degree angles to
let the water over them. Experiment finished, no data, no biological lesson.
I’d still love to do that experiment, but I just don’t know how to engineer it
myself.

The Experimental
outcome – no experiment

So, I took a risk, and my design did not work,
so the experiment flopped, literally on its side. On the plus side, the total
cost was maybe $1000 in materials and three people’s time for 5 days to build it.
Low cost, high possible reward, high risk. Did I make the right decision to try
this? Perhaps not, but it was exciting while it lasted and makes a fun story.

Vignette 2: When ‘dragons’ – specifically, trout
– ate my graduate student’s experiment. My student Brian Lohman and I planned a
study in which we would capture individual fish and collect detailed data on
their microhabitat at the capture location – then mark and release them. We’d
do that for a month, every day, all over a small 4 hectare lake (different one
than above). Hopefully we’d get multiple captures of many individuals,
obtaining detailed measures of individual movement distances and habitat use.
Then we could use a habitat map to evaluate the role of habitat choice in
dispersal decisions within a single lake. Things went swimmingly for weeks – it
was wet and windy and grey, but otherwise Brian was able to mark a large number
of fish. But as time went on, and the number of recaptures stayed at less than 10, he
was puzzled. Then, on the first sunny calm day he could finally see what was
going on below the surface of the water. Some local trout had apparently
learned to associate his small boat with the periodic arrival of momentarily
disoriented stickleback. Fish after fish was released back at their capture
site, only to be instantly eaten. Not something we had ever experienced before
or thought to anticipate, but the end result was too few recaptured (surviving)
fish to execute the intended study.

Vignette 3: My ‘Stark’ mistakes – or
‘misStarks’: hypotheses I thought would be correct, but ultimately proved to be
unsupported. There are quite a few of these. And reassuringly, many are
published – you can publish negative results. I’ll pick one example that I find
most instructive. In 2009 I had dinner with Rob Knight, and over wine
afterwards we compared our research projects (I talked about individual diet
variation in natural populations, he talked about diet effects on gut
microbiota in humans and lab mice). We conceived of a simple side-project collaboration:
I take an already-existing sample of 200 stickleback from one day in one lake,
and get stable isotope data from each individual to characterize their diets. I
send Rob DNA extracted from their intestines, and he uses next generation
sequencing to characterize their gut microbiota. Then we ask whether
among-individual diet variation in wild vertebrates correlates with
among-individual variation in gut microbiota. We knew how to execute each lab
step, and had done it before. We had the samples in hand. All systems go. Then,
when we had the data, the first pass analysis found no significant effect of
individual diet (carbon or nitrogen isotope ratio as the metric) and individual
microbiota composition. To give you an idea of how odd this was, let me point
out that there are tons of studies in humans and mice showing that diet changes
the microbiota. This was such an accepted thing, that everyone I talked to
about this just said “well of course it’ll work, but it’ll certainly be cool to
show this in a wild population for once” – or some variant on that sentiment.
But, no significant effect.

After some head-scratching, the reason for our
false expectation became clear: although sex had little significant effect on
the microbiota, and diet had no significant effect on the microbiota, there was
a strong sex*diet interaction. Basically, diet alters the microbiota in males,
and in females, but it does so differently in each sex so that in a mixed
sample (even keeping sex as a factor), the diet effect is obscured. So, our
initial expectation failed because something more subtle was going on (Bolnick
et al 2014 Nature Communications).

This particular story illustrates the point that
sometimes our failures are because we over-simplified, and if we dig a bit deeper
we discover something even more interesting. That’s not to say every failure to
reject a null hypothesis leads to some more interesting and subtle insight.
Sometimes our alternate hypotheses are truly incorrect, or at least not
supported in any way. I’ve put out substantial effort in some studies only to
get ambiguous results or no significant support for a core hypothesis (Ingram
et al 2011).

Vignette 4: My most embarrassing Great-House
failure, however, is just now making itself clear. I’ve collected stickleback
for 17 years almost now, and have dissected large numbers of wild-caught fish
to determine sex, obtain stomach contents, or examine parasite loads. In all
that time, I would frequently dissect fish whose internal organs were oddly
fused together – like someone had injected glue inside. I didn’t really know
what to make of it, so I ignored it. But now, that overlooked observation is turning
out to be a key feature of a story my lab is building up at the moment and
approaching publication. Rather than spoil the surprise, I’ll leave the details
for another post when this paper is done and published – suffice to say, there
are cool biological processes under our noses, and we sometimes just pass them
by because we are so busy with our pre-planned agenda.

I suppose the moral
of vignette 4 is to remain observant of the natural history of your system, to
avoid missing the proverbial “White Walker in the Room”. Ask questions about
oddities that you notice, even if it is not in your planned linear trajectory.
Constant vigilance! Because it might be something really neat that you are just
about to pass by. Let’s face it, we spend so much of our time meticulously
planning our experiments to avoid Viserys or Wise Masters type mistakes, and we
spend money and time pursuing large sample sizes so we minimize the risk of
statistical errors. But the best laid experimental design also generates some
blinders that may stop us from noticing the things we never even thought to ask
questions about.

To put this all together, I hope it is clear
that there are many ways we can fail in science, and that some failures are to
be expected – you just don’t know in advance which experiments will fail, and
in what way. But sometimes you have a pretty good idea which might fail. That’s
not a reason to abandon all hope – sometimes it is worth trying anyway, just in
case. Just keep a broad portfolio of studies so you always have a variety of
levels and types of risk of failure – that way something will pan out. Speaking
of which, (this being the day after I started writing this post), I should be
hearing momentarily from my crew whether the 690 fish survived the drive north.
I’ll keep you posted. In the meantime, please feel free to respond to this post
by putting in comments of any field or lab experiments of your own that just
crashed and burned.